nvm VS pyenv

Node.js + Nvm - runtime for javascript without a browser

Install Node.js if it hasn't been installed. There are several ways to install Node.js. You may download the installer from the official website, or install it with tools like NVM. After installation, run this command to verify its installation.

Our server also needs Node.js to run our app. We could install the binary directly, but I prefer to use a tool called NVM, which allows us to easily manage Node versions. We can install it with this command:

By setting up your environment in isolation, you can prevent yourself from a lot of issues when experimenting with code. It makes your code behave more predictable due to the defined state of the runtime environment you are working with. This article should provide you with enough information to get started, but obviously, there is a lot more power embedded in NVM, Virtual Environment and RBEnv. So make sure to check their documentation.

I highly recommend setting up nodejs with a version manager, nvm was and still is a popular option, however, I now recommend and have been using fnm, a simpler and faster alternative to manage my nodejs versions.

The purpose of a version manager is to help you navigate or install any tools for development easily. Version Manager can be one tool for each dependency (e.g. NVM, g) or One tool for all dependencies (e.g. asdf, mise).

I usually develop on Windows so I installed NVM for Windows from here, but if you’re on other OS I’m sure you can find a version that supports it, probably this is the answer.

This was a very quick introduction to how I setup NodeJS on my environment using nvm. If you have any questions please refer to the official documentation or contact me via my Social Links.

Source: Can this be used to create/download npm as a standalone executable? #3237.

For more information visit: pyenv repository

Note that virtual environments assume you are using the same global version of Python. Often, this is not the case and additional tools like pyenv can be used alongside virtual environments when you need to switch between versions of Python itself on your local machine.

Python version manager pyenv

First of all, install the Python virtual environment from these links: 1 and 2. I developed my GPT-based API in Python version 3.8.18. Pick any Python versions >= 3.7.

Note: Most modern systems will probably have a system environment that meets this requirement, but if yours does not or if you prefer not to install anything in your system environment (even if it's just PDM) check out asdf or pyenv to help install and manage additional Python environments.

When dealing with software development, reproducibility is key. This is why we encourage you to use Python virtual environments to set up an isolated environment for your project. Virtual environments allow the isolation of dependencies, which plays a crucial role to avoid breaking compatibility between different projects. We cannot cover all the details about virtual environments in this post, but we encourage you to learn more about venv, pyenv or conda for a better understanding on how to create and manage virtual environments.

For Python, with your use case I would avoid system packages, no matter the distro. It sounds like it would be worth setting up pyenv and working exclusively with virtual environments.

For OSX there is homebrew or pyenv (pyenv is another solution on Linux). As pyenv compiles from source it will require setting up XCode (the Apple IDE) tools to support this which can be pretty bulky. Windows users have chocolatey but the issue there is it works off the binaries. That means it won't have the latest security release available since those are source only. Conda is also another solution which can be picked up by Visual Studio Code as available versions of Python making development easier. In the end it might be best to consider using WSL on Windows for installing a Linux version and using that instead.